class_docstr: A fit of the LiFE model to diffusion data
docstr: Parameters
  ----------
  fiber_model : A FiberModel class instance
  
  params : the parameters derived from a fit of the model to the data.
docstr_tok: ["Parameters","--","--","--","--","--","fiber_model",":","A","FiberModel","class","instance","params",":","the","parameters","derived","from","a","fit","of","the","model","to","the","data","."]
code: def __init__(
      self,
      fiber_model,
      life_matrix,
      vox_coords,
      to_fit,
      beta,
      weighted_signal,
      b0_signal,
      relative_signal,
      mean_sig,
      vox_data,
      streamline,
      affine,
      evals,
  ):
      """
      Parameters
      ----------
      fiber_model : A FiberModel class instance
  
      params : the parameters derived from a fit of the model to the data.
  
      """
      ReconstFit.__init__(self, fiber_model, vox_data)
  
      self.life_matrix = life_matrix
      self.vox_coords = vox_coords
      self.fit_data = to_fit
      self.beta = beta
      self.weighted_signal = weighted_signal
      self.b0_signal = b0_signal
      self.relative_signal = relative_signal
      self.mean_signal = mean_sig
      self.streamline = streamline
      self.affine = affine
      self.evals = evals
  
imports: import numpy
  import scipy.sparse
  import scipy.linalg
  from dipy.reconst.base import ReconstModel, ReconstFit
  from dipy.tracking.utils import unique_rows
  from dipy.tracking.streamline import transform_streamlines
  from dipy.tracking.vox2track import _voxel2streamline
  import dipy.data
  import dipy.core.optimize
label_desc: Use image node_id 1 to create a new FiberFit object from inherited base classes: ReconstFit with example: obj = FiberFit(fiber_model, life_matrix, vox_coords, to_fit, beta, weighted_signal, b0_signal, relative_signal, mean_sig, vox_data, streamline, affine, evals)